Bridging the Chasm: Why Companies Need an AI Business Researcher (Chief AI Value Officer)
OK, how many of us have seen people think that AI is a silver bullet? This is something that has happened in the past and it is repeating itself now. Buy AI and it will solve your problems. That isn’t the case. Trillions of dollars are being invested globally, yet for many organizations, the promise of value remains elusive. Even adoption isn’t what it could be. Does this mean AI has no value and shouldn’t be invested in? The lack of value derived from AI can leave people frustrated and ready to leave the AI ship behind.
The answer to deriving value may lie in a critical, missing link within the corporate structure. The world has AI Researchers pushing the technical boundaries of models and algorithms, who possess strong technical and mathematical skills. On the business side, we have skilled business leaders focused on quarterly targets. But who is relentlessly researching the intersection of AI and core business strategy? How much is this gap impacting bottom line returns on AI investments? Does this area necessitate a new job role in a company?
It’s time to introduce a new, essential role designed specifically to bridge this gap: the AI Business Researcher.
The Missing Link: AI Business Research vs. AI Technical Research
While AI is powerful and AI researchers do much for the advancement of this world, that doesn’t necessarily guarantee a translation to business success. We know and respect the vital position of the AI Researcher. They are highly technical specialists—mathematicians, programmers, and engineers—who advance the state-of-the-art. The mission of the AI Researcher isn’t necessarily to push the limits of AI purely for the business. In fact, how many AI Researchers have a background in business?
The AI Business Researcher is a wholly different proposition. This role is non-technical in its execution but deeply strategic in its scope. How comfortable are people in deriving business value from AI? How many people understand the business enough to select the right AI solutions for the business to succeed? How many people truly went to school to understand and know the in’s and out’s of AI? The majority of people didn’t and so we need to see the intersection of AI technical and business strategy.
The Mission: Unlocking Value, Not Just Power
The AI Business Researcher (or perhaps, at the executive level, the Chief AI Value Officer) is the organization’s dedicated strategic scout. Their role is to be a dedicated AI and business strategist. They need to understand both the in’s and out’s of AI and the business, including the limitations and also the timing of using AI (it isn’t needed for every solution). Their mission is not to build the AI, but to select AI that proves valuable to the business.
1. Research and Translation (The Bridge)
This role lives at the forefront of AI trends—Large Language Models (LLMs), multimodal AI, embodied AI, etc.—but views them through a business lens. They don’t just know what an LLM is; they consistently research how that specific architecture could radically redefine the customer service pipeline, automate a core legal process, or create a new product category for the business. They translate technical breakthroughs into tangible business hypotheses.
2. Hypothesis Generation and Validation (The Freedom)
The greatest impediment to AI value is the fear of failure and the pressure of immediate ROI. This role needs the freedom to research. They are tasked with generating high-value hypotheses—not simply implementing what others have done—and designing non-technical experiments to validate them.
Example Hypothesis: “If we integrate a generative AI model into our internal knowledge base, we can reduce the average time-to-answer for Tier 2 support by 40%.”
Their job is to structure the experiment, define the success metrics, and prove the business case before a technical team is tasked with a costly build-out.
3. The Value Roadmap (The Strategy)
This officer is responsible for tying AI investment directly to corporate objectives. They are the ones who can look at a 5-year strategy and identify 3-5 specific AI applications that will serve as the catalysts for that strategy, creating organizational alchemy, moving the organization beyond simple cost-cutting to true competitive differentiation.
What This Role Means for Your Organization
Bringing an AI Business Researcher or Chief AI Value Officer into your structure can deliver immediate and profound returns:
Stops Wasteful Investment: By rigorously researching and proving the value hypothesis before technical resources are deployed, you stop investing millions in projects that look cool but lack a true ROI.
Accelerates Adoption: This officer acts as the AI evangelist and educator for the C-suite and the business units, making the complex accessible and the valuable undeniable.
Uncovers Non-Obvious Opportunities: The greatest value in AI often lies in areas where traditional efficiency methods have failed. This focused research can reveal opportunities (e.g., using vision models for quality control in manufacturing, or generative AI for hyper-personalized marketing) that are invisible to non-specialized leaders.
Future-Proofs the Strategy: This role guarantees that your organizational strategy is always informed by, and optimized for, the rapidly changing capabilities of artificial intelligence.
The AI technical team needs to push the limits of technology. The business team needs to push the limits of revenue. The AI Business Researcher is the one who ensures those limits are the same limits.
If an organization is investing heavily in AI but feeling a persistent disconnect between spend and strategic success, it may be time to stop hiring more programmers and start hiring a dedicated AI Business Researcher. The value of AI to a business may not be found in a model’s code; it may be found in the strategic mind capable of translating that code into business gold.